1,720,990 research outputs found
Adaptive tracking of multiple non rigid objects in cluttered scenes
No full textTracking of non-rigid objects (e.g. humans) is a crucial application for understanding the behavior of objects. Different methods have been presented in literature, whose main drawback is low robustness or high computational load in analysis of cluttered scenes. In the paper a low computational algorithm for tracking non-rigid objects in cluttered scenes is presented. The proposed approach models the shape of the objects by using corners. A learning algorithm is introduced in order to automatically extract the model of the object from a short video sequence acquired immediately before merging of more objects in the scene. The adaptive model extraction mechanism strongly improves method robustness. The method is tested on an existing video-surveillance system in order to track moving objects in cluttered scenes. Results show that the proposed approach gives good performances with low-processing times
Real-time robust detection of moving objects in cluttered scenes
No full textObject recognition is a very important task in computer vision and different techniques have been presented to solve it. In this paper a Hough-type low-computational algorithm for detection of objects in cluttered scenes is presented. The approach is based on the detection of the shape of an object, modeled by means of a set of corners. An automatically model learning method is introduced. The method is used in an existing video-surveillance system in order to increase its detection performances. Results show that the proposed approach provides good performances with low processing times
ROC curves for performance evaluation of video sequences processing systems for surveillance applications
No full textPerformance evaluation of image processing intermediate results in video based surveillance systems is extremely important due to the variety of approaches to this task. An approach based on the use of receiver operating characteristics (ROC) curves in order to evaluate the performance of a vision complex system for surveillance purposes is presented. The ROC curves have already been used in other research fields such as in the comparison of edge detection algorithms or in the evaluation of artificial neural networks: in this case they are used in order to compare different parameters selections within a system for the localization of moving objects. The presented results show the possibility of using ROC curves as a means for evaluation and comparison of video based surveillance systems
Adaptive post-processing error concealment based on feedback from a video-surveillance system
No full textAn effective real-time post-processing algorithm for error recovery in noise corrupted JPEG bit streams integrated into an existing remote video-surveillance system is presented(1). The algorithm exploits information extracted by the video-surveillance system in order to detect corrupted frames and to recover them, enhancing the performances of the system, without compromising the real-time behavior of the application. Results show the validity of the presented approach
Allocation strategies for distributed video surveillance networks
No full textThis paper discusses a typical architecture of a third generation surveillance system (3GSS). In particular a method for choosing the optimal distribution of intelligence required by 3GSSs is presented. Experimental results over a simulated system illustrate the presented approach
Real-time change detection methods for video-surveillance systems with mobile camera
No full textIn this paper, a video-surveillance system based on a mobile-camera is presented. The proposed real-time method is able to detect an object in a video sequence from a non-static camera. In particular during an off-line phase the system creates a panoramic multi-layer background image. In the on-line phase the system compares the acquired images with a portion of the panoramic background. Different change detection methods are analyzed. Experimental results are presented in order to validate the proposed methods. The proposed method could be used for extending efficient algorithms for scene understanding already developed and tested for fixed cameras to a mobile camera environment
Use of higher-order moments and related distribution series expansions for noise characterisation and performance evaluation in few-user asynchronous DS/CDMA systems
No full textThis work aims at proposing a higher-order moments analysis, in order to obtain an effective characterisation (in a non-Gaussian sense) of the global DS/CDMA noise in the case of few-user systems and short spreading codes. The use of the Edgeworth series expansion, whose terms are directly linked with the statistical cumulants allows to reach a good approximation of the unknown probability density function of the global DS/CDMA noise. The results concerning the DS/CDMA BER obtained by using the Edgeworth expansion are then compared with the ones provided by the Gram-Charlier series, and by other higher-order-moment-based approximations already presented in literature.This work aims at proposing a higher-order moments analysis, in order to obtain an effective characterisation (in a Non-Gaussian sense) of the global DS/CDMA noise in case of few-user systems and short spreading codes. The use of the Edgeworth series expansion, whose terms are directly linked with the statistical cumulants allows to reach a good approximation of the unknown probability density function of the global DS/CDMA noise. The results concerning the DS/CDMA BER obtained by using the Edgeworth expansion are then compared with the ones provided by the Gram-Charlier series, and by other higher-order-moment-based approximations already presented in literature
Change detection methods for automatic scene analysis by using mobile surveillance cameras
No full textThis paper proposes a video-surveillance system based on a mobile camera. In particular the developed system creates (during the off-line phase) a panoramic multilayer background image allowing one to use common change detection algorithms to search for a change detection binary image. Different approaches to get the change detection images are presented. The performances of the implemented algorithms are presented by using ROC curves
Distributed architectures and logical-task decomposition in multimedia surveillance systems
No full textIn the past few years, the development of complex surveillance systems has captured the interest of both the research and industrial worlds. Strong and challenging requirements of modern society are involved in this problem, which aims to increase safety and security in several application domains such as transport, tourism, home and bank security, military applications, etc. At the same time, fast improvements in microelectronics, telecommunications, and computer science make it necessary to consider new perspectives in this field. The main objective of this paper is to investigate, discuss, and evaluate the impact of distributed processing and new communication techniques on multimedia surveillance systems, which represent the so-called third-generation surveillance systems (3GSSs). In particular aspects related to the distribution of intelligence among multiple-processing and wide-bandwidth resources are discussed in detail. It is shown how distribution of intelligence can be obtained by a hierarchical architecture that partitions, in a dynamic way, the main logical processing tasks (i.e., representation, recognition, and communication) performed in a 3GSS physical architecture made lip of intelligent cameras, hubs, and central control rooms. The advantages of this solution are pointed out in terms of: 1) increased flexibility and reconfigurability and 2) optimal allocation of available processing and bandwidth resources. Finally, a case study is analyzed that allows one to gain a deeper insight into a distributed surveillance system
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